Using learning analytics systems for educational policies

This case focuses on the opportunity that micro - data on learning processes (e.g. within universities) and the use of learning analytics provide for the design of educational strategies by policy makers at a national and European level

Type of content: Assets
Type of asset:
Use case
Big data potential
Phase in the policy cycle:
Policy Design and Analysis
Open license availability
SWOT Analysis for
Using learning analytics systems for educational policies
Helpful Harmful
Strengths• Improve efficiency and effectiveness of their organisation
• Present data about learners in a usable form, either through visualisations or by summarizing and describing the data.
• Providing useful opportunities for reflecting on work that has been carried out and for making comparisons between individual learners, specific cohorts or institutions
Weaknesses• More empirical evidence is needed about the effects of learning analytics, in order to support a process of quality assurance
• Comparability of the data depending on standardisation, their consistency over time, and their overall reliability and quality.
• Lack of clear vision on the purpose of learning analytics in education, and guidance and frameworks on the use of learning analytics
• Lack of leadership for the implementation and monitoring of learning analytics
• Lack of student involvement, particularly when it comes to data protection
• Insufficient skills and training in using learning analytics or analysing resulting data.
• Stakeholder engagement needs to be increased by reaching out to groups including teachers, students, staff, employers and parents.
• As legislation changes and individuals become more aware of data use, institutions need help to understand their responsibilities and obligations regarding data privacy and data protection.
• The coherence between data sets in terms of scope and definitions. Micro-data sets such as the ones resulting from learning analytics are built to satisfy the needs at an institutional level which does not always coincide with the needs and intended use of these data at national or European level.
Opportunities• Learning analytics has the potential to contribute to the quality of teaching and learning and the modernisation of educational systems in Europe
• Increased amount of data available in education (due to data collected in Learning Management Systems, online education, social media and the increased use of digital technology more generally in education). Students “digital footprint” is growing.
Threats• Data protection, ownership and control of data are amongst the most challenging areas of learning analytics, in particular if commercial companies are involved in the process
• Data storage and access need to be looked at more closely and the approaches of different countries could provide best practices
• Inclusion of countries and regions with a weak educational data system or lower levels of online

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